Lead Data Engineer

Data Engineer IV Location: Remote (PST Preferred) Duration: 7-Month Contract (Through April 16, 2027) Employment Type: Contract | 40 Hours per Week Start Date: ASAP Pay rate: $110/hr. - $118/hr. on W2 About the Opportunity A Global Leading Technology Company is seeking an experienced Data Engineer IV to support critical data infrastructure and analytics initiatives within its AI and Product Ecosystem organization. This role offers the opportunity to work on cutting-edge AI and GenAI-driven products, building the data foundations that power insights, product decisions, and large-scale user experiences. The ideal candidate will be responsible for designing scalable data solutions, developing robust data pipelines, ensuring data quality, and creating impactful reporting and dashboarding capabilities. This position requires strong technical expertise, exceptional collaboration skills, and a passion for solving complex data challenges in a fast-paced environment. Team & Project Overview This role supports a high-impact AI-focused organization responsible for developing and maintaining end-to-end data architecture that drives reporting, analytics, and measurement across AI-powered products and services. The team is focused on enabling scalable growth through robust data infrastructure, advanced reporting capabilities, and innovative AI-driven engineering practices. The Data Engineer IV will collaborate with cross-functional partners to ensure data systems are reliable, scalable, and capable of supporting rapidly evolving product needs. Key Responsibilities Design, develop, and maintain scalable data pipelines and ETL processes. Build and support reliable data infrastructure that enables analytics, reporting, and product insights. Partner closely with data scientists, analysts, product managers, and engineering teams to deliver high-quality data solutions. Implement and maintain data quality frameworks, automated monitoring, and anomaly detection processes. Develop dashboards, reports, and analytical solutions that support business decision-making and product performance tracking. Build and validate product logging systems to ensure accurate and reliable data collection. Leverage AI-native tools and workflows to improve productivity and accelerate data engineering delivery. Troubleshoot, diagnose, and resolve data-related issues in a timely manner. Document data workflows, architecture, processes, and best practices. Contribute to operational excellence through knowledge sharing and process improvements. Required Qualifications Bachelor's degree in Computer Science, Engineering, Mathematics, or a related technical field, or equivalent practical experience. 7+ years of experience in Data Engineering, Data Warehousing, or a related discipline. Strong expertise in SQL and Python for large-scale data processing and analytics. Hands-on experience designing, building, and maintaining ETL/ELT pipelines. Experience developing and implementing data quality, validation, and monitoring frameworks. Experience creating dashboards, reporting solutions, and analytics products. Strong understanding of data modeling, data governance, and scalable data architecture. Experience working with cloud platforms such as AWS, Google Cloud Platform, or Azure. Experience with modern data warehousing technologies such as Snowflake, Redshift, BigQuery, or similar platforms. Excellent analytical, problem-solving, and troubleshooting skills. Strong communication, collaboration, and stakeholder management abilities. Preferred Qualifications Previous experience working within large-scale consumer technology environments. Familiarity with AI-native analytics, data engineering, and developer productivity tools. Experience supporting AI/ML or Generative AI product ecosystems. Experience building data solutions that support large-scale product metrics and user insights.

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